Niche Radius Adaptation with Asymmetric Sharing
Niche Radius Adaptation with Asymmetric Sharing
复制标题
具有不对称共享的利基半径适应
DOI：
10.1007/978-3-540-87700-4_20
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Thomas Bäck
中科院分区：
文献类型：
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作者：
Vincent van der Goes;O. M. Shir;Thomas Bäck
在遗传算法领域，已经发明了小生境技术，目的是在多模式适应度景观上诱导物种。不幸的是，它们通常依赖于问题相关的生态位半径参数。这就是生态位半径问题。在最近的研究中，人们研究了将小生境技术转移到进化策略(ES)领域的可能性。最初的尝试是通过自适应来学习生态位半径的良好值。本文提出了一种自适应生态位半径的ES小生境方法：非对称共享。这是健身分享的一种形式。与以前的研究不同，它不依赖于生态位半径与其他策略参数的耦合。实验结果表明，与传统共享相比，非对称共享具有更好的性能，不依赖于问题相关的参数。
In the field of Genetic Algorithms, nichingtechniques have been invented with the aim to induce speciationon multimodal fitness landscapes. Unfortunately, they often rely on a problem-dependent niche radiusparameter. This is the niche radius problem. In recent research, the possibilities to transfer niching techniques to the field of Evolution Strategies(ES) have been studied. First attempts were carried out to learn a good value for the niche radius through self-adaptation. In this paper we introduce a new niching method for ES with self-adaptation of the niche radius: asymmetric sharing. It is a form of fitness sharing. In contrast to earlier studies, it does not depend on coupling the niche radius to other strategy parameters. Experimental results indicate that asymmetric sharing performs well in comparison to traditional sharing, without relying on problem-dependent parameters.